1. Field of the Invention
The invention relates generally to systems that detect the presence of a human being in a space of interest, and more particularly, to automatic detection of occupant status of a vehicle seat, i.e., whether the seat is occupied with a human being, or whether the seat is occupied with a non-human being (e.g., a box or a bag), or whether the seat is empty; determination when the seat is occupied by a human being whether the occupant is seated normally or leaning; determination of the presence of one or more human beings hidden or hiding within an enclosed space, such as a trailer, a cave, or an underground bunker; location of persons or animals trapped in a hazardous or hostile environment; and determination of the drowsiness of a human engaged in a dangerous task, such as the operation of an automobile or truck.
2. Discussion of the Related Art
In order that a front-seat passenger in a vehicle be protected in the event of a collision, motor vehicles are equipped with a front-seat passenger airbag. A necessary, but not entirely sufficient, condition for airbag deployment is that the front passenger seat be occupied. There are a number of systems for determining the presence of a human being in a vehicle seat. A typical detection system available in the art includes one or more sensing devices for measuring predetermined characteristics of a seat occupant. The sensed characteristics are used to determine whether a vehicle seat is occupied with a human subject, and further to determine whether to deploy the airbag. The weight of the occupant has been used in known arrangements as a fundamental parameter in this regard. More particularly, weight is used as a criterion to distinguish between a human-occupied seat and an empty seat. However, weight-based occupant detection systems have met challenges in calibration for different seat types, different operating environments, etc. There also are known systems for detecting occupancy of vehicle seats in which vision, infrared, or ultrasonic focal plane array sensors are used to gather occupant information. These sensors are mounted within the vehicle, but away from the seats, such as in the overhead console. However, since these sensors do not directly measure physical attributes they are not as reliable as those that do, and accordingly, occupant-sensing systems based on such sensors are more prone to errors than their weight-based counterparts. Occupant-sensing systems that use focal plane array technology also tend to be much more costly.
In another application of human being detection systems, unauthorized persons might endeavor to pass through entry checkpoints that have high security requirements (e.g., at airports, shipyards, border crossings, ballparks, concert halls, and secure or limited access areas such as military bases, power plants, nuclear plants, government buildings, etc.) by hiding, for example, in the trunk of an automobile or in a trailer. Conventional visual security checks are time-consuming and prone to fault due to human error and fatigue. An automatic human being presence detection system can reduce the workload for the guards and provide information about the inside of an enclosed space. An enclosed-space human being detection system developed at Lockheed Martin Energy Systems, Inc. detects the presence of human beings with geophones placed on the vehicle and employs wavelet analysis to the sensed data to determine if there are persons in the vehicle. This known system, as is the case with others, is capable of detecting human being presence, but it needs careful positioning and tuning of the sensors.
Enclosed spaces not only include boxed areas, but also areas that are hemispherical, tubular, etc. Examples of the other kind include caves, underground bunkers, tunnels, etc. A case in point is the ongoing anti-terrorism search for hidden/hiding criminals over the countryside and mountain ranges of certain foreign countries. The system proposed herein is useful in locating and capturing human beings who are hidden or hiding in caves, underground bunkers, tunnels, etc.
There is a need for a human being presence detection system that locates human beings buried under rubbles, trapped behind barriers, or inside buildings. After a disaster strikes, such as an earthquake, a hurricane, or a terrorist attack, human beings might be buried or trapped under rubble or behind large barriers. Similarly, there is a need to find human beings trapped indoors during a building fire. Rapid location of such persons can reduce the loss of life.
In a “life-detection system,” human subjects are illuminated by penetrating microwave, and the reflected wave is modulated by the body movements, including the breathing and heartbeat. In this arrangement, the human being presence detection is accomplished by extracting the breathing and heartbeat component signals from the received microwave signal.
Drowsiness is a common attribute of humans engaged in repetitive monotonous tasks. When the task is, for example, the operation of an automobile or truck, the consequences of undetected drowsiness can be fatal. Previous approaches to the detection of drowsiness have relied on measuring eye closure, i.e., so-called “perclose.” Although perclose can be a reliable measure of human drowsiness, it cannot be reliably estimated in operating conditions and requires very careful calibration for each human.
Heartbeat and breathing signals have been extensively used in detecting and monitoring human beings. In one known arrangement the author proposed a hand-held acoustic sensor pad that is placed on the subjects' upper chest to monitor heartbeat and breathing patterns. Since the water-filled sensor is excellently coupled with the human body, it is able to collect high signal-to-noise ratio heartbeat and breath signals. In another known arrangement, the life detection system utilizes active microwave sensors to acquire the heartbeat and breathing signals with a high signal-to-noise ratio. In both these cases, the acquired signal clearly shows the breathing and heartbeat patterns in time domain.